Freie Universität Berlin: Handle and analyze real-world event streams
公司规模
1,000+
地区
- Europe
国家
- Germany
产品
- Streaming Analytics Education Package (SAEP)
技术栈
- Streaming Analytics
- Real-time Data Processing
实施规模
- Departmental Deployment
影响指标
- Digital Expertise
- Innovation Output
技术
- 分析与建模 - 大数据分析
- 分析与建模 - 实时分析
适用行业
- 教育
适用功能
- 产品研发
用例
- 实时定位系统 (RTLS)
服务
- 数据科学服务
关于客户
Freie Universität Berlin, founded in 1948, is one of Germany's leading research universities and the highest ranked. It is one of the German Excellence Universities that has succeeded in all three funding lines in the federal and state Excellence Initiative. Additionally, Freie Universität Berlin was one of nine German top universities to win in the German Universities Excellence Initiative, a national competition for universities organized by the German Federal Government. The university recognized the need for data scientists early on and decided to use the SAEP to help students become specialists in the field of event processing and analytics.
挑战
As big, fast data proliferates, more and more data streams are being generated in real time from a myriad of data sources, such as Internet of Things (IoT) sensors, markets, mobile devices, internal transactional systems and clickstream analysis. Real-time insights must be derived from this data to give a competitive edge to agile organizations that want to act on these insights before they lose their value. To handle billions of these data streams, new software architectures and techniques are needed. These types of software are called “Big Data Streaming Analytics.” Companies need educated specialists to harness the power of big data. The Streaming Analytics Education Package (SAEP) is Software AG´s answer to the growing demand for data science experts. Universities and private companies share the responsibility of training the sought-after talent currently demanded by the market.
解决方案
The Streaming Analytics Education Package (SAEP) is designed to be a full-term independent study project, enabling students to handle and analyze real-world event streams. The SAEP contains streaming analytics software, enabling informed decisions to be made at speed and scale by integrating realtime analytics and decisioning into transaction executing systems. University students use the “Soccer Scenario,” one of the case studies included in the SAEP. It requires the students to analyze position data of both, players and ball, in a soccer game and generate information about the game as results in a dashboard. The scenario includes 50 million data sets recorded using sensors mounted on soccer players’ shoes and gloves as well as on the ball.
运营影响
数量效益
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